Rapid motion estimation and correction using self-encoded FID navigators in 3D radial MRI

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Diagnostics play a pivotal role in nuclear fusion experimental reactors, supporting physical studies, modelling, and plasma control. However, most diagnostics provide limited and partial information about the plasma's status. For instance, magnetic probes ...

We propose a test -time adaptation for 6D object pose tracking that learns to adapt a pre -trained model to track the 6D pose of novel objects. We consider the problem of 6D object pose tracking as a 3D keypoint detection and matching task and present a mo ...

Deep heteroscedastic regression involves jointly optimizing the mean and covariance of the predicted distribution using the negative log-likelihood. However, recent works show that this may result in sub-optimal convergence due to the challenges associated ...

Tightly-coupled sensor orientation, i.e. the simultaneous processing of temporal (GNSS and raw inertial) and spatial (image and lidar) constraints in a common adjustment, has demonstrated significant improvement in the quality of attitude determination wit ...

VR (Virtual Reality) is a real-time simulation that creates the subjective illusion of being in a virtual world. This thesis explores how integrating the user's body and fingers can be achieved and beneficial for the user to experience VR. At the advent of ...

The theory underlying robust distributed learning algorithms, designed to resist adversarial machines, matches empirical observations when data is homogeneous. Under data heterogeneity however, which is the norm in practical scenarios, established lower bo ...

In this work, we systematically evaluate the accuracy in band gap prediction of range-separated hybrid functionals on a large set of semiconducting and insulating materials and carry out comparisons with the performance of their global counterparts. We obs ...

We study the problem of estimating an unknown function from noisy data using shallow ReLU neural networks. The estimators we study minimize the sum of squared data-fitting errors plus a regularization term proportional to the squared Euclidean norm of the ...

Ever growing pixel acquisition rates in the fields of augmented reality, autonomous driving and robotics have increased interest in solid state beam scanning without moving parts. Modern photonic integrated laser ranging advances towards passive beam steer ...

The thesis at hand is concerned with robots' navigation in human crowds. Specifically, methods are developed for planning a mobile robot's local motion between pedestrians, and they are evaluated in experiments where a robot interacts with real pedestrians ...

Context. We report the exploitation of a sample of Solar System observations based on data from the third Gaia Data Release (Gaia DR3) of nearly 157 000 asteroids. It extends the epoch astrometric solution over the time coverage planned for the Gaia DR4, w ...

Out-of-body experiences (OBEs) are characterized by the subjective feeling of being located outside one's physical body and perceiving one's own body from an elevated perspective looking downwards. OBEs have been correlated with abnormal integration of bod ...

Long term human motion prediction is essential in safety-critical applications such as human-robot interaction and autonomous driving. In this paper we show that to achieve long term forecasting, predicting human pose at every time instant is unnecessary. ...

The forced response of rigid rotors, supported by herringbone-grooved gas journal bearings are investigated numerically and experimentally. The rotor configurations are varied by using end cylinders, attached at both sides of the shaft. Three rotors with d ...

Detecting people from 2D images and analyzing their motion in 3D have been long standing computer vision problems central to numerous applications such as autonomous driving and athletic training. Recently, with the availability of large amounts of trainin ...

We consider a least-squares/relaxation finite element method for the numerical solution of the prescribed Jacobian equation. We look for its solution via a least-squares approach. We introduce a relaxation algorithm that decouples this least-squares proble ...

This paper introduces a new method for solving the distributed AC power flow (PF) problem by further exploiting the problem formulation. We propose a new variant of the ALADIN algorithm devised specifically for this type of problem. This new variant is cha ...

This paper considers the multi-agent linear least-squares problem in a server-agent network architecture. The system comprises multiple agents, each with a set of local data points. The agents are connected to a server, and there is no inter-agent communic ...

Quantitative magnetic resonance imaging (qMRI) can increase the specificity and sensitivity of conventional weighted MRI to underlying pathology by comparing meaningful physical or chemical parameters, measured in physical units, with normative values acqu ...

In airborne laser scanning a high-frequency trajectory solution is typically determined from inertial sensors and employed to directly geo-reference the acquired laser points. When low-cost MEMS inertial sensors are used, such as in lightweight unmanned ae ...

Rapid motion estimation and correction using self-encoded FID navigators in 3D radial MRI

Chattez avec Graph Search

Time-resolved, physics-informed neural networks for tokamak total emission reconstruction and modelling

Test-time adaptation for 6D pose tracking

TIC-TAC: A Framework for Improved Covariance Estimation in Deep Heteroscedastic Regression

Airborne sensor fusion: Expected accuracy and behavior of a concurrent adjustment

From finger animation to full-body embodiment of avatars with different morphologies and proportions

Robust Distributed Learning: Tight Error Bounds and Breakdown Point under Data Heterogeneity

Range-separated hybrid functionals for accurate prediction of band gaps of extended systems

Near-Minimax Optimal Estimation With Shallow ReLU Neural Networks

Chaotic microcomb inertia-free parallel ranging

Geometric and Learning Methods for Robots to Navigate in Human Crowds with Application to Smart Mobility Devices

Gaia Focused Product Release: Asteroid orbital solution: Properties and assessment

Out-of-body illusion induced by visual-vestibular stimulation

Long Term Motion Prediction Using Keyposes

Experimental and numerical investigation of the unbalance behavior of rigid rotors supported by spiral-grooved gas journal bearings

Encoder-Decoder Models for Human Segmentation and Motion Analysis

A Least-Squares Method for the Solution of the Non-smooth Prescribed Jacobian Equation

Rapid Scalable Distributed Power Flow with Open-Source Implementation

Iterative pre-conditioning for expediting the distributed gradient-descent method: The case of linear least-squares problem

Variability and reproducibility of multi-echo T2 relaxometry: Insights from multi-site, multi-session and multi-subject MRI acquisitions

On the benefit of concurrent adjustment of active and passive optical sensors with GNSS & raw inertial data